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机构地区:[1]北京师范大学中国基础教育质量监测协同创新中心
出 处:《教育测量与评价》2017年第3期12-16,共5页Educational Measurement and Evaluation
基 金:国家社会科学基金2012年度项目"基于学生发展的学校自我诊断研究"(项目编号:12BGL099)的主要研究成果之一
摘 要:在基于学生发展的学校自我诊断中,有效运用大数据是实现科学诊断的关键。首先,通过指数算法,判断学校在核心要素上的目标达成度;其次,通过关联横纵数据,找准关键问题,全面深入分析数据以挖掘学校的优势和问题;再次,通过多角度的数据互证,发现问题的实质和突破口;最后,结合多种形式的数据,如师生的主观留言、访谈及课堂观察等,寻找问题改进的策略与方法。四个环节层层深入,并持续追踪大数据的发展,可以帮助学校清晰地描绘出发展进步的轨迹。In the process of school self-diagnosis based on students' development, the effective use of big data is the key to achieve scientific and effective diagnosis. Firstly,we could judge the schools’goal achievements on the core factors by computing the factor index. Secondly, through comprehensively and deeply analyzing the cross-sectional and longitudinal data,we could find the advantages and disadvantages of schools. Thirdly,we could find the essence and the breakthrough of school’s problems by cross-validation from different perspective data. Finally,we could explore out the strategies and methods of school improvement combined with various forms of data,such as teachers and students’ subjective item answers, interview, classroom observation and so on. These four processes through which we could help school clearly describe their development and progress trajectory are layer upon layer combing with tracking the development of diagnosis data.
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